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Axiomatizing Causal Reasoning
Author(s) -
Joseph Y. Halpern
Publication year - 2000
Publication title -
journal of artificial intelligence research
Language(s) - English
Resource type - Book series
SCImago Journal Rank - 0.79
H-Index - 123
eISSN - 1943-5037
pISSN - 1076-9757
ISBN - 1-55860-555-X
DOI - 10.1613/jair.648
Subject(s) - pearl , causality (physics) , class (philosophy) , causal model , causal reasoning , mathematics , computer science , algebra over a field , calculus (dental) , artificial intelligence , pure mathematics , psychology , statistics , philosophy , cognition , medicine , physics , theology , dentistry , quantum mechanics , neuroscience
Causal models defined in terms of a collection of equations, as defined by Pearl, are axiomatized here. Axiomatizations are provided for three successively more general classes of causal models: (1) the class of recursive theories (those without feedback), (2) the class of theories where the solutions to the equations are unique, (3) arbitrary theories (where the equations may not have solutions and, if they do, they are not necessarily unique). It is shown that to reason about causality in the most general third class, we must extend the language used by Galles and Pearl (1997, 1998). In addition, the complexity of the decision procedures is characterized for all the languages and classes of models considered.

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